Various data capture methods and techniques are available to capture hand-written data from paper forms. Typically, the paper form is scanned on a scanner to produce an electronic format of the paper form in the computer. Thereafter a software application processes the hand-written text data and extracts therefrom all of the hand-written text data.
While the process of data capture is a straightforward process, it is considered a tedious task for a business organization dealing with numerous paper forms. Since, business organizations process large quantities of handwritten or machine printed data forms in order to accomplish their business objectives, data capture remains a problematic and expensive endeavor for such business organizations.
Lately, crowdsourcing has emerged as an important and economical labor pool for business organizations. Crowdsourcing provides a promising solution for performing voluminous human intelligence tasks such as video analysis, image labeling, etc. However, the shortcoming in applying crowdsourcing for data entry of paper forms is that when the paper form containing sensitive or confidential information is presented to crowdsourced workers, the sensitive or confidential information may be viewed by the crowdsourced workers and could possibly be misused.
Therefore, there is a need to provide an efficient method and system for processing paper forms for data entry.